In analyzing a very large data set, it is frequently desirable to calculate multiple statistics that characterize the data in the set. Calculating accurate summary statistics for a large data set often requires not only that every data point to be processed, but also requires significant amounts of memory for storing the results of intermediate computations, sorted subsets, and other elements and structures used during the process. When common algorithms are used to compute various statistics, the amount of processing and intermediate storage often times may change substantially as a function of the size and cardinality of the data set.